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| Construction and verification of nomogram prediction model of risk for perineal laceration in primiparas |
| ZHANG Han1 DUAN Xia1 PANG Qiying2 MAO Yanli3 ZHONG Minhui1 YU Chan1 YAN Xiaoxue1#br# |
1.Department of Nursing, the First Maternity and Infant Hospital, Tongji University, Shanghai 201204, China;
2.Department of Neurology, Huashan Hospital, Fudan University, Shanghai 200040, China;
3.Department of Anesthesiology, Tenth People’s Hospital of Tongji University, Shanghai 200072, China |
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Abstract Objective To construct the nomogram prediction model of risk for perineal laceration in primiparas. Methods A total of 932 primiparas from the First Maternity and Infant Hospital, Tongji University from December 2020 to September 2021 were selected as research objects. A total of 746 primiparas were used as the modeling group to construct the model, and they were divided into laceration group (506 cases) and non-laceration group (240 cases) according to whether perineal laceration occurred; 186 primiparas were included in validation group to validate the model. Logistic regression model was used to construct the model, Hosmer-Lemeshow goodness of fit, calibration curve, and receiver operating characteristic curve were used to evaluate the model. Results The first labor time, second labor time, and total labor time in laceration group were longer than those in non-laceration group, and the differences were statistically significant (P < 0.05). The proportion of full-term birth, suspected macrosomia, epidural analgesia, midwife outpatient service, fetal distress, and hypertension of pregnancy in laceration group was higher than that in non-laceration group, and the difference was statistically significant (P < 0.05); there were significant differences in perineal elasticity, length of perineal body, degree of puerperal cooperation, seniority of midwife, mode of induced labor, free position, delivery position, degree of fear of childbirth, and physical activity level during pregnancy between two groups (P < 0.05). Gestational age， suspected macrosomia, second labor time, degree of fear of childbirth, seniority of midwives, and physical activity level during pregnancy were the influencing factors of perineal lacerations in primiparas (P < 0.05). The Hosmer-Lemeshow goodness of fit and calibration curve indicated that the model fit was good. The area under the curve of the modeling group and the verification group were 0.822 and 0.799, respectively， and the prediction performance of the model was good. Conclusion The prediction model of risk for perineal laceration in this study has good differentiation and calibration, which can provide an efficient and convenient evaluation tool for clinical practice.
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